Mixed-reality (MR) soundscapes blend real-world sound with virtual audio from hearing devices, presenting intricate auditory information that is hard to discern and differentiate. This is particularly challenging for blind or visually impaired individuals, who rely on sounds and descriptions in their everyday lives. To understand how complex audio information is consumed, we analyzed online forum posts within the blind community, identifying prevailing challenges, needs, and desired solutions. We synthesized the results and proposed Sound Unblending for increasing MR sound awareness, which includes six sound manipulations: Ambience Builder, Feature Shifter, Earcon Generator, Prioritizer, Spatializer, and Stylizer. To evaluate the effectiveness of sound unblending, we conducted a user study with 18 blind participants across three simulated MR scenarios, where participants identified specific sounds within intricate soundscapes. We found that sound unblending increased MR sound awareness and minimized cognitive load. Finally, we developed three real-world example applications to demonstrate the practicality of sound unblending.

翻译：混合现实（MR）声音景观将真实世界的声音与听力设备的虚拟音频相融合，呈现出难以辨别和区分的复杂听觉信息。这对盲人或视障患者尤其具有挑战性，因为他们日常生活中依赖声音与描述。为理解复杂音频信息的接收方式，我们分析了盲人社区的网络论坛帖子，识别了当前面临的挑战、需求及理想解决方案。通过综合研究结果，我们提出"声音去混叠"方法以增强MR声音感知，该方法包含六种声音操控技术：环境构建器、特征位移器、音标生成器、优先级排序器、空间化器和风格化器。为评估声音去混叠的有效性，我们在三种模拟MR场景中开展用户研究，邀请18名盲人参与者从复杂声景中识别特定声音。研究发现声音去混叠能提升MR声音感知并降低认知负荷。最后，我们开发了三个真实应用案例以验证声音去混叠的实用性。